改进自适应双门限协作频谱感知算法

Improved Adaptive Double-Threshold Cooperative Spectrum Sensing Algorithm

频谱感知是认知无线电领域的关键技术之一,得到了众多学者广泛深入的研究。在低信噪比情况下,传统双门限算法阈值门限固定不变导致检测效果较差,针对该问题,提出一种自适应双门限协作频谱感知算法,通过计算各节点信噪比得到权值,调整判决门限,将当前判决结果与前后时刻充分联系,融合各节点判决信息得到最终判决结果,理论分析和仿真结果表明,相较于传统双门限和加权双门限检测算法,本文提出的算法具有更好的检测效果。

As one of the key technologies of cognitive radio,spectrum sensing is extensively and deeply studied.In the case of low SNR environment,the threshold of traditional double threshold method is fixed,which leads to poor perception effect.To solve the problem,an adaptive double-threshold cooperative spectrum sensing algorithm is proposed.The weight is obtained by calculating the SNR of each node.The weights are obtained.The decision threshold is adjusted,and the current judgment result is fully correlated with the time before and after,and the final decision result is obtained by fusing the decision information of each node.The results of theoretical analysis and Monte-Carlo simulation show that the algorithm can effectively improve the spectrum sensing performance compared with the traditional double threshold detection algorithm and the weighted double threshold detection algorithm.